Associations between cardiorespiratory fitness and lifestyle‐related factors with DNA methylation‐based ageing clocks in older men: WASEDA'S Health Study

Abstract

DNA methylation‐based age estimators (DNAm ageing clocks) are currently one of the most promising biomarkers for predicting biological age. However, the relationships between cardiorespiratory fitness (CRF), measured directly by expiratory gas analysis, and DNAm ageing clocks are largely unknown. We investigated the relationships between CRF and the age‐adjusted value from the residuals of the regression of DNAm ageing clock to chronological age (DNAmAgeAcceleration: DNAmAgeAccel) and attempted to determine the relative contribution of CRF to DNAmAgeAccel in the presence of other lifestyle factors. DNA samples from 144 Japanese men aged 65–72 years were used to appraise first‐ (i.e., DNAmHorvath and DNAmHannum) and second‐ (i.e., DNAmPhenoAge, DNAmGrimAge, and DNAmFitAge) generation DNAm ageing clocks. Various surveys and measurements were conducted, including physical fitness, body composition, blood biochemical parameters, nutrient intake, smoking, alcohol consumption, disease status, sleep status, and chronotype. Both oxygen uptake at ventilatory threshold (VO ₂/kg at VT) and peak oxygen uptake (VO ₂/kg at Peak) showed a significant negative correlation with GrimAgeAccel, even after adjustments for chronological age and smoking and drinking status. Notably, VO ₂/kg at VT and VO ₂/kg at Peak above the reference value were also associated with delayed GrimAgeAccel. Multiple regression analysis showed that calf circumference, serum triglyceride, carbohydrate intake, and smoking status, rather than CRF, contributed more to GrimAgeAccel and FitAgeAccel. In conclusion, although the contribution of CRF to GrimAgeAccel and FitAgeAccel is relatively low compared to lifestyle‐related factors such as smoking, the results suggest that the maintenance of CRF is associated with delayed biological ageing in older men.

Abstract

The contribution of cardiorespiratory fitness (CRF) to GrimAgeAcceleration and FitAgeAcceleration are relatively low compared to lifestyle‐related factors such as serum triglyceride, daily intake of carbohydrate, smoking, and calf circumference. There is a negative correlation between CRF and GrimAgeAcceleration, even after adjusting for chronological age, smoking, and alcohol consumption, and maintenance of CRF above reference values is negatively correlated with delayed GrimAgeAcceleration.